Graduate School of Psychology
R
ESEARCHM
ASTER’
SP
SYCHOLOGYM
ASTERT
HESISUnfolding psychosis: resting-state functional connectivity of the
fronto-striatal network in schizophrenia offspring
Merel W. Keizer
Student number
: 5960436
Specialization
: Brain & Cognition
ResMas supervisor
: Ilja Sligte, PhD
External supervisor
: Matthijs Vink, PhD
Second assessor
: Mike Cohen, PhD
Research location
: University Medical Center Utrecht, department of psychiatry
Abstract
Schizophrenia is a debilitating disorder, characterized by a dysfunctional fronto-striatal network. Important cognitive functions regulated by this network, are impaired in schizophrenia patients, such as working memory, inhibitory control and reward processing. These impairments have been linked to abnormal brain activity in the fronto-striatal network in schizophrenia. Similar deficits are also found in siblings of schizophrenia patients, implying a genetic disposition. It is suggested that aberrant functional connectivity found in schizophrenia is associated with these impairments. Here, we investigate whether disturbances of the fronto-striatal network are present already during adolescence in children at familial risk for schizophrenia, before the onset or treatment of the illness. Resting-state fMRI data were obtained from 17 schizophrenia offspring, and 34 healthy controls (age range 9-19). In healthy controls, functional connectivity increased with age between the right ventral striatum and respectively the right ACC and right DLPFC. Functional connectivity did not increase in the schizophrenia offspring group for any of the selected fronto-striatal connections. Moreover, with increasing age, functional connectivity diverged for healthy controls and schizophrenia offspring between the left ventral striatum and the left ACC, as well as between the right ventral striatum and respectively the right ACC, and right DLPFC. These results indicate impaired development of the functional organization of the fronto-striatal network in schizophrenia offspring before the onset of a potential psychosis. Also, these findings are consistent with impaired cognitive functions found in schizophrenia patients, their unaffected siblings and offspring. To conclude, impaired functional connectivity of the fronto-striatal network could be a risk factor for developing schizophrenia.
Introduction
Schizophrenia often produces a lifetime of disability and emotional distress for affected individuals (Lewis & Lieberman, 2000). The clinical symptoms of schizophrenia are characterized by hallucinations and delusions (positive symptoms), and social withdrawal, poverty of speech and flat affect (negative symptoms) (Gogtay et al., 2011). Schizophrenia is commonly seen as a neurodevelopmental disorder (Lewis & Levitt, 2002). Developmental brain abnormalities may originate during the prenatal period and continue through childhood and adolescence (Weinberger, 1987). Importantly, previous research has shown that schizophrenia is characterized by a dysfunctional fronto-striatal network (Pantelis et al., 1997; Vink et al., 2006). Clinically, negative symptoms have been associated with frontal hypo-activation (Lahti et al., 2001), while increased impulsivity and psychosis has been linked to striatal hyper-activation (Howes et al., 2007; Lee et al., 2009). Furthermore, schizophrenia patients show cognitive impairments in domains that are regulated by the fronto-striatal network (Spear, 2011), such as poor inhibitory control and working memory (Zandbelt et al., 2011), and impaired reward processing (Heinz and Schlagenhauf, 2010; Juckel et al., 2006).
A widely accepted model for deficits in the fronto-striatal network in schizophrenia is the dopamine hypothesis (Weinberger et al., 2001). This hypothesis states that dysfunction of the prefrontal cortex in schizophrenia is associated with abnormal prefrontal dopamine signaling. Animal studies found that dopamine activity in the striatum is regulated by feedback from prefrontal cortex. Consequently, dysfunctional downstream projections from the prefrontal cortex to the striatum results in disinhibition of striatal dopamine (Weinberger et al., 2001). In turn, increased dopamine neuronal activity in the striatum is related to psychosis (Howes et al., 2007; Lee et al., 2009; Weinberger et al., 2001). Consequently, dopamine has been an important component when trying to explain schizophrenia and its symptoms.
More recently, previous research has also focused on relatives of schizophrenia patients. Unaffected siblings of schizophrenia patients show similar deficits to schizophrenia patients in cognitive functions associated with aberrant frontal and striatal functioning, such as working memory (de Leeuw et al., 2013), inhibition (Kumari et al., 2005; Raemaekers et al., 2005), and reward (de Leeuw et al., 2014). The fronto-striatal abnormalities that are observed in unaffected siblings demonstrate that these deficits are likely linked to a genetic predisposition. Also, children of parents with schizophrenia are genetically
vulnerable, with an increased risk of 15% to develop schizophrenia (Gottesman, 1991). Cross-sectional studies with offspring of schizophrenia patients also show disturbances in the fronto-striatal network during working memory tasks (Bakshi et al., 2011; Diwadkar et al., 2011a) and sustained attention (Diwadkar et al., 2012, 2011b). Furthermore, structural studies have indicated reduced connectivity in schizophrenia. Studies show reduced white matter (Dougherty et al., 2012; Francis et al., 2013) and cortical surface (Prasad et al., 2010) in subcortical regions and frontal cortex in schizophrenia offspring, and abnormal white matter connectivity in young never-medicated schizophrenia patients (Mandl et al., 2013). However, a decrease in structural connectivity does not necessarily imply a decrease in functional connectivity (Koch et al., 2002). These results support the notion of a lack of connectivity in the brain in schizophrenia patients and individuals at familial risk for schizophrenia. Importantly, results of aberrant brain activity found in relatives and unmedicated schizophrenia patients are not confounded by medication or expression of the disorder in the brain.
Like many of the major neuropsychiatric illnesses, schizophrenia has a typical age of onset in late adolescence (Spear, 2000). Alongside environmental changes, adolescence is a critical period in brain development, making it particularly vulnerable for the onset of psychopathology. Studies show that the frontal cortex matures later than subcortical structures, such as the striatum (Sowell, Thompson, Holmes, Jernigan, & Toga, 1999; Spear, 2000). Furthermore, typical adolescent behavior, such as impulsivity and risk taking (Paus et al., 2008), indicates a temporary imbalance in the fronto-striatal network. During adolescence, the frontal cortex matures and the imbalance of the fronto-striatal network diminishes with age, as the activity and connectivity of the network increases (Vink et al., 2014). The network becomes balanced and integrated (Crone and Dahl, 2012; Somerville and Casey, 2010). Schizophrenia patients, their unaffected siblings and offspring show aberrant fronto-striatal activity and impaired cognitive functions regulated by this network. This could suggest impaired restoration of the imbalance that exists during adolescence of the fronto-striatal network in schizophrenia offspring. Moreover, characteristic prefrontal dysfunction in schizophrenia patients, unaffected siblings and offspring supports the notion that the frontal cortex is already dysfunctional at onset of adolescence. Here, it is suggested that an underdeveloped frontal cortex at onset of adolescence affects the ability to make effective connections with the striatum during adolescence. Consequently, the imbalance of the fronto-striatal network seen in
healthy adolescence may be exaggerated in schizophrenia offspring at the onset of adolescence, which will hinder development of functional connectivity of the frontal-striatal network during adolescence.
Taken together, behavioral results, cognitive impairments, hypo-activation of fronto-cortical regions, and decreased structural connectivity suggest that there is decreased functional connectivity in the fronto-striatal network in schizophrenia and high-risk relatives. Previous studies with schizophrenia patients, their siblings and offspring suggest that disturbances in the frontal-striatal network develop during adolescence. A failure of the fronto-striatal network to develop properly during adolescence could put individuals at risk for developing schizophrenia. However, functional connectivity of the frontal-striatal network in young adolescents at familial risk for schizophrenia has not yet been investigated.
Resting-state activity is a way to investigate the intrinsic functional architecture of the human brain, and is independent of task-related activity. Therefore, in order to gain insight in the etiology of schizophrenia, we investigated resting-state functional connectivity of the fronto-striatal network in adolescent schizophrenia offspring. We hypothesized that there is decreased functional connectivity between the frontal cortex and the striatum in adolescent schizophrenia offspring compared to healthy controls. The regions of interest (ROIs) that were selected in the frontal cortex are the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), and anterior cingulate cortex (ACC). The ROIs in the striatum are the ventral striatum, dorsal caudate and putamen (see Figure 1). The effect of age on functional connectivity between frontal and striatal areas was examined. We expected that resting-state functional connectivity between the frontal cortex and striatum would not increase during adolescence in schizophrenia offspring, while in healthy controls there would be an increase in functional connectivity with age in this network. Also, we expected that functional connectivity during resting state between the frontal cortex and striatum would be lower at the onset of adolescence in schizophrenia offspring compared to healthy controls.
Methods Participants
Nineteen at-risk children with one schizophrenia parent were recruited via the high-risk outpatient clinic at the University Medical Centre (UMC) Utrecht. Parents were diagnosed with schizophrenia according to
the DSM-IV. Forty-three healthy control children were recruited via advertisements and schools. All participants were right-handed. Children were excluded if they had a comprehensive disease history, or take medication for psychosis-related symptoms. Moreover children were also not included in the study if they had an IQ below 70. All participants and their parents provided written informed consent and the children received payment for their participation.
Eleven participants (nine controls, two schizophrenia offspring) were excluded from analyses due to excessive head movement in the scanner (> 3 mm in any direction). After exclusion of these participants, the schizophrenia offspring group consisted of 11 females and 6 males, with a mean age of 13.77 (SD = 2.92, range 9-18 years). The healthy control group consisted of 15 females and 19 males, with a mean age of 13.48 (SD = 1.94, range 10–17 years).
Image acquisition
Imaging was performed on a Philips 3.0 Tesla Achieva whole-body MRI scanner (Philips Medical Systems, Best, The Netherlands). Functional images were obtained using a two-dimensional echo planar imaging (EPI-SENSE) sequence with the following parameters: repetition time = 1600 ms, echo time = 23.5 ms, field of view 208 x 120 x 256, flip angle = 72.5˚, 4x4 mm in-plane resolution, 4 mm slice thickness, 30 slices per volume, SENSE-factor = 2.4). The fMRI scanning was carried out in darkness, participants were instructed to keep their eyes closed and not think of anything in particular. A single run of 300 functional images was acquired over a period of eight minutes. T1-weighted anatomical data were obtained for within-subject registration purposes.
fMRI preprocessing
Image preprocessing was performed using SPM 8 (fil.ion.ucl.ac.uk/spm). Preprocessing included slice-time correction, realignment to the mean functional image, coregistration to the anatomical image, normalization to an MNI T1-standard brain, and spatial smoothing with a Gaussian kernel (8 mm full width at half maximum).
Functional connectivity analysis
To compute functional connectivity maps (FC maps) based on Regions of Interest (ROIs), we first made a mask with 3 frontal (ACC, DLPFC, VLPFC) and 3 striatal (dorsal caudate, putamen and ventral striatum) areas (see Figure 1). Functional connectivity analyses were conducted using toolbox REST (Resting-State fMRI Data Analysis Toolkit, restfmri.net), with plug-in program DPARSF (Data Processing Assistant for Resting-State fMRI, rfmri.org/DPARSF). Analysis of the data entailed a band pass filter (0.01-0.08 Hz) to reduce low frequency drift, high frequency respiratory and cardiac noise. Also, the white matter signal and cerebrospinal fluid signal were regressed out from BOLD signals. Next, the averaged time course was obtained from the ROIs.
ROI analysis
Pearson correlation coefficients between the averaged time course of the striatal and frontal ROIs within the same hemisphere were calculated (ROI-wise analysis). A Fisher r-to-z transform was used for each participant to form a normalized FC map. Finally, a linear regression analysis with group and age as independent variables was performed with the FC maps. The regression tested functional connectivity for each group with separate age slopes, and also the main effect of age and group on functional connectivity. Group differences in the functional connectivity-age relationship were tested in an interaction test between age and group. To test for differences in resting-state functional connectivity at the onset of adolescence (under 14 year), independent samples t-test were performed. Significance for statistical results was thresholded at p-value ≤ 0.008, Bonferroni corrected for multiple ROIs.
Figure 1. Regions of interest (ROIs) used in the left hemisphere (coordinates in standard space above). The same
ROIs were used for the right hemisphere. 1 = ACC (anterior cingulate cortex), 2 = DLPFC (dorsolateral prefrontal cortex), 3 = VLPFC (ventrolateral prefrontal cortex), 4 = putamen, 5 = ventral striatum, 6 = dorsal caudate.
Results
Regression analysis based on ROIs with group and age as between factors revealed that resting-state functional connectivity increased over age in healthy controls between the right ventral striatum and respectively the right ACC (F(1,33) = 13.54, r = 0.55, p < 0.001) and the right DLPFC (F(1,33) = 9.17, r = 0.47, p = 0.004), while it did not increase in the schizophrenia offspring group for any of the selected fronto-striatal connections (see Table 1). There were no main effects for group or age. However, regression analysis did reveal interactions between group and age for the functional connection between the left ventral striatum and the left ACC (F(1,47) = 8.46, p = 0.0055), as well as between the right ventral striatum and respectively the right ACC (F(1,47) = 11.77, p = 0.001), and right DLPFC (F(1,47) = 14.53, p < 0.001)(see Table 2). Results of functional connectivity over age between the ROI pairs are visualized in Figure 2. Furthermore, independent samples t-tests showed that there were no differences in resting-state functional connectivity under the age of 14 between schizophrenia offspring and healthy controls (see Table 2).
Table 1. Age slope coefficients and accompanying p-values of functional connectivity (FC) for healthy
controls and schizophrenia offspring. * Denotes significant p-values for uncorrected threshold of p ≤ 0.05. ** Denotes significant p-values for adjusted threshold of p ≤ 0.008. L = left, R = right, ACC = anterior cingulate cortex, DLPFC = dorsolateral prefrontal cortex, VLPFC = ventrolateral prefrontal cortex.
Table 2. Test statistics and accompanying p-values of functional connectivity (FC). * Denotes significant p-values for uncorrected threshold of p ≤ 0.05. ** Denotes significant p-values for adjusted threshold of p
≤ 0.008. L = left, R = right, ACC = anterior cingulate cortex, DLPFC = dorsolateral prefrontal cortex, VLPFC = ventrolateral prefrontal cortex.
Figure 2. Resting-state functional connectivity between the frontal cortex and striatum across age.
* Indicates significant interactions between group and age. ACC = anterior cingulate cortex, DLPFC = dorsolateral prefrontal cortex, VLPFC = ventrolateral prefrontal cortex, CI = confidence interval.
Discussion
Here, we investigated resting-state functional connectivity of the fronto-striatal network in adolescents at familial risk for schizophrenia and healthy controls. In line with the hypothesis, some brain areas showed increased functional connectivity during resting state over age in healthy adolescents, while this was not observed for schizophrenia offspring in any of the selected functional connections in the fronto-striatal network. Specifically, functional connectivity between the right ventral striatum and respectively the right ACC and right DLPFC increased over age in healthy adolescents. Moreover, the relationship between increasing age and functional connectivity differed for the schizophrenia offspring and healthy controls for three fronto-striatal connections. Specifically, with increasing age, functional connectivity diverged for the two groups between the right ventral striatum and respectively the right ACC and right DLPFC, as well as between the left ventral striatum and the left ACC. Consequently, these results show that
schizophrenia offspring is less able to make effective functional connections in areas of the fronto-striatal network during adolescence compared to healthy controls. However, contrary to expectations, results showed no differences in resting-state functional connectivity in schizophrenia offspring compared to healthy controls under the age of 14. This does not support the idea of underdeveloped functional connectivity at the onset of adolescence in schizophrenia offspring.
The current findings are consistent with previous studies with schizophrenia offspring that showed impaired cognitive functions that are governed by this network, such as working memory (Bakshi et al., 2011; Diwadkar et al., 2011a) and sustained attention (Diwadkar et al., 2012, 2011b). Moreover, decreased functional connectivity in schizophrenia offspring is congruent with the finding of reduced structural connectivity in these subjects (Francis et al., 2013; Prasad et al., 2010). Finally, the current results are also consistent with similar neural and associated cognitive deficits found in schizophrenia patients and unaffected siblings, such as impaired working memory (de Leeuw et al., 2013; Pantelis et al., 1997), inhibition (Kumari et al., 2005; Vink et al., 2006), and reward (de Leeuw et al., 2014; Murray et al., 2008).
The subjects of this study span a long range of adolescence. Therefore, the current results give a unique insight in potential neurodevelopmental abnormalities in non-prodromal individuals at risk for psychosis. The failure to develop functional connections in schizophrenia offspring is observed between especially the ventral striatum and respectively the DLPFC and the ACC, and to a larger extent in the right hemisphere. These aberrant functional connections are based on resting-state activity in the brain, and are therefore not dependent on specific task-related activity. This indicates that the intrinsic functional organization of the brain is affected during brain development in adolescents at familial risk for schizophrenia. Functional connectivity is especially aberrant in three areas of the fronto-striatal network.
Firstly, the ventral striatum has shown to be essential in reward processing, which is impaired in schizophrenia patients (Heinz and Schlagenhauf, 2010) and unaffected siblings (de Leeuw et al., 2014). Regarding the dopamine hypothesis, the current results suggest that dysfunctional dopamine-mediated reward pathways in schizophrenia, including the ventral striatum and the frontal cortex, are related to impaired development of functional connectivity during adolescence in schizophrenia offspring. Specifically, functional dysfunctions between the ventral striatum and respectively the ACC, and DLPFC could be implicated in the pathology of psychotic illnesses. Second, fronto-striatal dysfunction has been
linked to poor working memory in schizophrenia patients and unaffected siblings and offspring (de Leeuw et al., 2013; Diwadkar et al., 2011a; Pantelis et al., 1997; Zandbelt et al., 2011). Especially the DLPFC has been shown to be imperative to working memory (Curtis and D’Esposito, 2003). The current results suggest compromised fronto-cortical communication between areas involved in executive functions such as working memory, in adolescents at familial risk for schizophrenia. Lastly, the ACC has been linked to cognitive functions such as sustained attention, reward anticipation and inhibition, which are affected in schizophrenia and adolescent schizophrenia offspring (Diwadkar et al., 2011b). Therefore, abberant functioning of the executive core found in schizophrenia patients and relatives could be mediated by a premorbid functional deficit in connectivity.
Taken together, an inability to make effective connections during adolescence suggests that aberrant functional organization of the brain contributes to neural and cognitive deficits in schizophrenia and high-risk relatives. In the current study, not all functional fronto-striatal connections were impaired in schizophrenia offspring compared to healthy controls. Therefore, this research revealed the most vulnerable pathways in adolescents at risk for schizophrenia. Accordingly, the goal was to provide an exploratory way to uncover impaired functional connections in a specific network of ROIs. However, a disadvantage of the current methods with the number of ROIs and number of participants, is loss of statistical power. Therefore, various other methods could be used in future research to help qualify affected functional connections in the brain of schizophrenia patients and relatives. Also, it is needed to determine how cognitive deficits operate with respect to the specific aberrant pathways that were found. Moreover, research with more at-risk subjects can provide specification regarding the age of onset of these disturbances. And lastly, following adolescent schizophrenia offspring into adulthood would provide essential information on the possible course to pathology of psychotic illness. Therefore, longitudinal studies are required in order to gain insight in the etiology of schizophrenia.
In sum, we found impaired resting-state functional connectivity in parts of the fronto-striatal network in adolescent schizophrenia offspring, before the onset of a psychosis and use of medication. Specifically, functional connections between the ventral striatum and respectively the ACC and DLPFC were affected. Therefore, this study provides insight in the manner that increased familial risk for schizophrenia impacts the development of the fronto-striatal network during a critical period of
maturation of the brain. The results suggest unique vulnerability pathways in adolescent schizophrenia offspring. Consequently, impaired development of functional connectivity of the fronto-striatal network could be a risk factor for developing schizophrenia.
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